Cocrystal Synthesis through Crystal Structure Prediction

Crystal structure prediction (CSP) is an invaluable toolin thepharmaceutical industry because it allows to predict all the possiblecrystalline solid forms of small-molecule active pharmaceutical ingredients.We have used a CSP-based cocrystal prediction method to rank ten potentialcocrystal coformers by the energy of the cocrystallization reactionwith an antiviral drug candidate, MK-8876, and a triol process intermediate,2-ethynylglyclerol. For MK-8876, the CSP-based cocrystal predictionwas performed retrospectively and successfully predicted the maleicacid cocrystal as the most likely cocrystal to be observed. The triolis known to form two different cocrystals with 1,4-diazabicyclo[2.2.2]octane(DABCO), but a larger solid form landscape was desired. CSP-basedcocrystal screening predicted the triol-DABCO cocrystal as rank one,while a triol-l-proline cocrystal was predicted as rank two.Computational finite-temperature corrections enabled determinationof relative crystallization propensities of the triol-DABCO cocrystalswith different stoichiometries and prediction of the triol-l-proline polymorphs in the free-energy landscape. The triol-l-proline cocrystal was obtained during subsequent targeted cocrystallizationexperiments and was found to exhibit an improved melting point anddeliquescence behavior over the triol-free acid, which could be consideredas an alternative solid form in the synthesis of islatravir.

Automated summary

Crystal structure prediction is an important tool in the pharmaceutical industry for predicting different solid forms of active pharmaceutical ingredients. Using a CSP-based cocrystal prediction method, we ranked potential cocrystal coformers for an antiviral drug and a process intermediate. The predictions were successful and resulted in the discovery of improved solid forms for synthesis.